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pmid:34337056

Identification of Multiple Hub Genes and Pathways in Hepatocellular Carcinoma: A Bioinformatics Analysis.

Junwei Liu · Fang Han · Jianyi Ding · Xiaodong Liang · Jie Liu · Dongsheng Huang · Chengwu Zhang

BioMed research international · 2021 doi:10.1155/2021/8849415

Paper

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Experiment

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Data

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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pmid:34337056
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science-record
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2026-11-01T15:41:46Z
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2026-11-01T22:04:24Z
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paper object · 10 fields
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title
Identification of Multiple Hub Genes and Pathways in Hepatocellular Carcinoma: A Bioinformatics Analysis.
doi
10.1155/2021/8849415
pmid
34337056
authors array · 7 items
[0]
Junwei Liu
[1]
Fang Han
[2]
Jianyi Ding
[3]
Xiaodong Liang
[4]
Jie Liu
[5]
Dongsheng Huang
[6]
Chengwu Zhang
journal
BioMed research international
year
2021
abstract
Hepatocellular carcinoma (HCC) is a common malignant tumor of the digestive system, and its early asymptomatic characteristic increases the difficulty of diagnosis and treatment. This study is aimed at obtaining some novel biomarkers with diagnostic and prognostic meaning and may find out potential therapeutic targets for HCC. We screen differentially expressed genes (DEGs) from the HCC gene expression profile GSE14520 using GEO2R. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were conducted by using the clusterProfiler software while a protein-protein interaction (PPI) network was performed based on the STRING database. Then, prognosis analysis of hub genes was conducted using The Cancer Genome Atlas (TCGA) database. Quantitative real-time polymerase chain reaction (qRT-PCR) was utilized to further verify the expression of hub genes and explore the correlation between gene expression and clinicopathological parameters. A total of 1053 DEGs were captured, containing 497 upregulated genes and 556 downregulated genes. GO and KEGG analysis indicated that the downregulated DEGs were mainly enriched in the fatty acid catabolic process while upregulated DEGs were primarily enriched in the cell cycle. Simultaneously, ten hub genes (CYP3A4, UGT1A6, AOX1, UGT1A4, UGT2B15, CDK1, CCNB1, MAD2L1, CCNB2, and CDC20) were identified by the PPI network. Five prognosis-related hub genes (CYP3A4, CDK1, CCNB1, MAD2L1, and CDC20) were uncovered by the survival analysis based on TCGA database. The ten hub genes were further validated by qRT-PCR using samples obtained from our hospital. The prognosis-related hub genes such as CYP3A4, CDK1, CCNB1, MAD2L1, and CDC20 could be considered potential diagnosis biomarkers and prognosis targets for HCC. We also use Oncomine for further verification, and we found CCNB1, CCNB2, CDK1, and CYP3A4 which were highly expressed in HCC. Meanwhile, CCNB1, CCNB2, and CDK1 are highly expressed in almost all cancer types, which may play an important role in cancer. Still, further functional study should be conducted to explore the underlying mechanism and biological effect in the near future.
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In the present study, we apply GEO2R (https://www.ncbi.nlm.nih.gov/geo/geo2r/), an online interactive analysis tool, which allows users to analyze the degree of data discrepancy between different groups in GEO to screen the DEGs between cancerous and noncancerous samples. To decrease the false positive rate, p values were adjusted in accordance with the Benjamini-Hochberg false discovery rate (FDR) method.
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sections[4] "2.2. Identification of DEGs" paragraph 2
quote
In the present study, we apply GEO2R (https://www.ncbi.nlm.nih.gov/geo/geo2r/), an online interactive analysis tool, which allows users to analyze the degree of data discrepancy between different groups in GEO to screen the DEGs between cancerous and noncancerous samples. To decrease the false positive rate, p values were adjusted in accordance with the Benjamini-Hochberg false discovery rate (FDR) method.
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complete
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All data generated or analyzed during this study are included in this article.
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sections[22] "Data Availability" paragraph 2
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All data generated or analyzed during this study are included in this article.
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Apply the paper's statistical method to the resolved series and compare the result with the published target.
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https://doi.org/10.1155/2021/8849415
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488
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null
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null
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3921;571
taxon
Homo sapiens
title
Gene expression data of human hepatocellular carcinoma (HCC)
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2026-11-01T15:39:54Z
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identifier_resolution_only_no_download_no_licence_read
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The detailed information and primer sequences of ten hub genes screened out by PPI networks.
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PMC8292096
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9
section_title
2.7. RT-qPCR Validation Analysis
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Table 1
caption
The detailed information and primer sequences of ten hub genes screened out by PPI networks.
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[0] array · 5 items
[0]
Category
[1]
Gene abbreviation
[2]
Description
[3]
Forward primer (5′-3′)
[4]
Reverse primer (5′-3′)
[1] array · 5 items
[0]
Upregulated
[1]
CDK1
[2]
Cyclin-dependent kinase 1
[3]
CAGGTCAAGTGGTAGCCATG
[4]
ACCTGGAATCCTGCATAAGC
[2] array · 4 items
[0]
CCNB1
[1]
Cyclin B1
[2]
AAGGCGAAGATCAACATGGC
[3]
CCAATGTCCCCAAGAGCTGT
[3] array · 4 items
[0]
MAD2L1
[1]
Mitotic arrest deficient 2 like 1
[2]
CGGTGACATTTCTGCCACTG
[3]
GGTCCCGACTCTTCCCATTT
[4] array · 4 items
[0]
CCNB2
[1]
Cyclin B2
[2]
CTGTACATGTGCGTTGGCAT
[3]
CTTGGAAGCCAAGAGCAGAG
[5] array · 4 items
[0]
CDC20
[1]
Cell division cycle 20
[2]
CAGCAGAAACGGCTTCGAAA
[3]
ACCCGAACATCATGGTGGTG
[6] array · 1 item
[0]
[7] array · 5 items
[0]
Downregulated
[1]
CYP3A4
[2]
Cytochrome P450 3A4
[3]
TGAAAGAAAGTCGCCTCGAA
[4]
CCAGATCGGACAGAGCTTTG
[8] array · 4 items
[0]
UGT1A6
[1]
Uridine diphosphate glucuronosyl transferase 1A6
[2]
CCGTGTTCCCTGGAGCATAC
[3]
AGGAAGTTGGCCACTCGTTG
[9] array · 4 items
[0]
AOX1
[1]
Alcohol oxidase 1
[2]
AATTCCTCAGCAAGTGCCCT
[3]
CGGAAGGCTGACACAAATTC
[10] array · 4 items
[0]
UGT1A4
[1]
Uridine diphosphate glucuronosyl transferase 1A4
[2]
TGCCATACTTTTTCTGCCCC
[3]
AACAGCCACACGGATGCATA
[11] array · 4 items
[0]
UGT2B15
[1]
Uridine diphosphate glucuronosyl transferase 2B15
[2]
CTGGAAGCTGTGGAAAGGTG
[3]
CACCTCATGACCCCTCTGAA
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section[9]/table-wrap[1]#tab1
[3] object · 16 fields
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section[14]/table-wrap[1]#tab2
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KEGG analysis of the down- and upregulated DEGs in HCC.
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PMC8292096
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14
section_title
3.2. GO Analysis and KEGG Enrichment Pathways of DEGs
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10
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6
table object · 8 fields
label
Table 2
caption
KEGG analysis of the down- and upregulated DEGs in HCC.
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[0] array · 6 items
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Category
[1]
ID
[2]
Description
[3]
Gene ratio
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p value
[5]
p.adjust
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[0]
Downregulated
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hsa05204
[2]
Chemical carcinogenesis
[3]
27/368
[4]
6.38E − 16
[5]
1.70E − 13
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[0]
hsa00071
[1]
Fatty acid degradation
[2]
19/368
[3]
4.55E − 14
[4]
3.02E − 12
[3] array · 5 items
[0]
hsa00982
[1]
Drug metabolism-cytochrome P450
[2]
23/368
[3]
2.03E − 13
[4]
1.08E − 11
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[0]
hsa04976
[1]
Bile secretion
[2]
19/368
[3]
8.13E − 10
[4]
2.16E − 08
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[0]
hsa03320
[1]
PPAR signaling pathway
[2]
19/368
[3]
1.06E − 09
[4]
2.55E − 08
[6] array · 1 item
[0]
[7] array · 6 items
[0]
Upregulated
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hsa04110
[2]
Cell cycle
[3]
11/83
[4]
1.04E − 07
[5]
2.03E − 05
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hsa03030
[1]
DNA replication
[2]
6/83
[3]
2.41E − 06
[4]
0.000234
[9] array · 5 items
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hsa00240
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Pyrimidine metabolism
[2]
7/83
[3]
0.000124
[4]
0.008017
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section[14]/table-wrap[1]#tab2
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asset:data:geo:GSE14520 not downloaded
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asset:data:geo:GSE14520 licence not read
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[0] object · 10 fields
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method-1
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survival_analysis
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kaplan_meier
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Survival analysis
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survival_km
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time_to_event_with_censoring
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Kaplan-Meier
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method-2
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survival_analysis
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Survival analysis
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logrank_test
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time_to_event_with_censoring
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centrality_scores
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protein-protein interaction
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GEO2R with Benjamini-Hochberg false discovery rate adjustment
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In the present study, we apply GEO2R (https://www.ncbi.nlm.nih.gov/geo/geo2r/), an online interactive analysis tool, which allows users to analyze the degree of data discrepancy between different groups in GEO to screen the DEGs between cancerous and noncancerous samples. To decrease the false positive rate, p values were adjusted in accordance with the Benjamini-Hochberg false discovery rate (FDR) method.
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complete
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meta_analysis
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survival_analysis
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pca
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network_analysis
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candidate
Automated Assays Laravel application and simulated adapters
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survival_km
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basis
The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: kaplan_meier.
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capability:computational_analysis
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The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here.
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GSE14520
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GSE14520
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All data generated or analyzed during this study are included in this article.
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The paper names GSE14520 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read.
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survival_km
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data:geo:GSE14520
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minimax
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pmid:34337056
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hub genes in hepatocellular carcinoma. 3.5. RT-qPCR Validation of Expression of Ten Hub Genes in
[1]
vels of these hub genes were obtained by the RT-qPCR experiment in 59 pairs of HCC and adjacent n
[2]
b genes in hepatocellular carcinoma. 3.5. RT-qPCR Validation of Expression of Ten Hub Genes in
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s of these hub genes were obtained by the RT-qPCR experiment in 59 pairs of HCC and adjacent n
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:34337056", "kind": "science-record", "revision": 7, "content_hash": "sha256:0967e822fe1e0e7b4c348e1dd6c5693cf0ed339de1eba44d0e016199eb1849e0", "created_at": "2026-11-01T15:41:46Z", "updated_at": "2026-11-01T22:04:24Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of Multiple Hub Genes and Pathways in Hepatocellular Carcinoma: A Bioinformatics Analysis.", "doi": "10.1155/2021/8849415", "pmid": "34337056", "authors": ["Junwei Liu", "Fang Han", "Jianyi Ding", "Xiaodong Liang", "Jie Liu", "Dongsheng Huang", "Chengwu Zhang"], "journal": "BioMed research international", "year": 2021, "abstract": "Hepatocellular carcinoma (HCC) is a common malignant tumor of the digestive system, and its early asymptomatic characteristic increases the difficulty of diagnosis and treatment. This study is aimed at obtaining some novel biomarkers with diagnostic and prognostic meaning and may find out potential therapeutic targets for HCC. We screen differentially expressed genes (DEGs) from the HCC gene expression profile GSE14520 using GEO2R. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were conducted by using the clusterProfiler software while a protein-protein interaction (PPI) network was performed based on the STRING database. Then, prognosis analysis of hub genes was conducted using The Cancer Genome Atlas (TCGA) database. Quantitative real-time polymerase chain reaction (qRT-PCR) was utilized to further verify the expression of hub genes and explore the correlation between gene expression and clinicopathological parameters. A total of 1053 DEGs were captured, containing 497 upregulated genes and 556 downregulated genes. GO and KEGG analysis indicated that the downregulated DEGs were mainly enriched in the fatty acid catabolic process while upregulated DEGs were primarily enriched in the cell cycle. Simultaneously, ten hub genes (CYP3A4, UGT1A6, AOX1, UGT1A4, UGT2B15, CDK1, CCNB1, MAD2L1, CCNB2, and CDC20) were identified by the PPI network. Five prognosis-related hub genes (CYP3A4, CDK1, CCNB1, MAD2L1, and CDC20) were uncovered by the survival analysis based on TCGA database. The ten hub genes were further validated by qRT-PCR using samples obtained from our hospital. The prognosis-related hub genes such as CYP3A4, CDK1, CCNB1, MAD2L1, and CDC20 could be considered potential diagnosis biomarkers and prognosis targets for HCC. We also use Oncomine for further verification, and we found CCNB1, CCNB2, CDK1, and CYP3A4 which were highly expressed in HCC. Meanwhile, CCNB1, CCNB2, and CDK1 are highly expressed in almost all cancer types, which may play an important role in cancer. Still, further functional study should be conducted to explore the underlying mechanism and biological effect in the near future.", "claims": [{"id": "claim-method", "statement": "In the present study, we apply GEO2R (https://www.ncbi.nlm.nih.gov/geo/geo2r/), an online interactive analysis tool, which allows users to analyze the degree of data discrepancy between different groups in GEO to screen the DEGs between cancerous and noncancerous samples. To decrease the false positive rate, p values were adjusted in accordance with the Benjamini-Hochberg false discovery rate (FDR) method.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34337056", "locator": "sections[4] \"2.2. 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